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A deep neural network based surrogate model for damage identification in full-scale structures with incomplete noisy measurements

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Frontiers of Structural and Civil Engineering 2024年第3期18卷 393-410页

作者： tram bui-NGOC Duy-Khuong LY tam t tRUONG Chanachai tHONGCHOM t.NGUYEN-tHOI Laboratory for Computational Mechanics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Civil Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Department of Computer Science Aarhus UniversityAarhus 8000Denmark thammasat University research unit in structural and foundation engineering Department of Civil EngineeringThammasat UniversityPathumthani 12120Thailand Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam thammasat School of Engineering Thammasat UniversityPathumthani 12120Thailand

the paper introduces a novel approach for detecting structural damage in full-scale structures using surrogate models generated from incomplete modal data and deep neural networks(DNNs).A significant challenge in this field is the limited availability of measurement data for full-scale structures,which is addressed in this paper by generating data sets using a reduced finite element(FE)model constructed by SAP2000 software and the MAtLAB programming *** surrogate models are trained using response data obtained from the monitored structure through a limited number of measurement *** proposed approach involves training a single surrogate model that can quickly predict the location and severity of damage for all potential *** achieve the most generalized surrogate model,the study explores different types of layers and hyperparameters of the training algorithm and employs state-of-the-art techniques to avoid overfitting and to accelerate the training *** approach’s effectiveness,efficiency,and applicability are demonstrated by two numerical *** study also verifies the robustness of the proposed approach on data sets with sparse and noisy measured ***,the proposed approach is a promising alternative to traditional approaches that rely on FE model updating and optimization algorithms,which can be computationally *** approach also shows potential for broader applications in structural damage detection.

关键词： vibration-based damage detection deep neural network full-scale structures finite element model updating noisy incomplete modal data

Suzuki Reaction of Aryl Bromides Using a Phosphine-Free Magnetic Nanoparticle-Supported Palladium Catalyst

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催化学报 2011年第11期32卷 1667-1676页

作者： Nghia t. bui trung B. DANG Ha V. LE Nam t. S. PHAN Department of Chemical Engineering HCMC University of Technology VNU-HCM 268 Ly Thuong Kiet Distriet 10 Ho Chi Minh City Viet Nam

A palladium catalyst immobilized on superparaganetic nanoparticles was prepared with a palladium loading of 0.30 mmol/g. the catalyst was characterized using X-ray diffraction, scanning electron microscopy, transmission electron microscopy, vibrating sample magnetometry, thermogravimetric analysis, Fourier transform infrared, atomic absorption spectrophotometry, and nitrogen adsorption. the immobilized palladium catalyst was an efficient catalyst without added phosphine ligands for the Suzuki cross-coupling reaction of several aryl bromides with phenylboronic acid. the recovery of catalyst was simply by magnetic decantation in the presence of a magnet. the immobilized palladium catalyst can be reused many times without significant degradation in catalytic activity. No leaching of active palladium species into the reaction solution was detected.

关键词： superparamagnetic nanoparticle Suzuki reaction palladium aryl bromide

Economic Sustainability Assessment of Groundwater Resources： Case Study of Hanoi, Vietnam

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Journal of Environmental Science and Engineering(B) 2017年第12期6卷 624-633页

作者： nuong thi bui Akira Kawamura Hideo Amaguchi Duong Du bui Ngoc tu truong Hoang Nam Nguyen Department of Civil and Environmental Engineering Tokyo Metropolitan University Tokyo 192-0397 Japan Water Resources Monitoring Department National Center for Water Resources Planning and Investigation Hanoi 100000 Vietnam the State Key Laboratory of Bioreactor Engineering East China University of Science & Technology Shanghai 200237 China Faculty of Urban and Environmental Natural Resource Economics & Management National Economics University Hanoi Vietnam

the most useful indicators should be established, designed and customized based on local issues of a target area. In order to establish groundwater sustainability indicators for the Vietnam capital, Hanoi, in this study, the sustainability assessment framework of groundwater resources from an economic perspective is proposed for the first time with the focus of Hanoi current groundwater problems. An AHP （Analytical Hierarchy Process） approach is employed to generate the main components （aspects and indicators） of this framework, because development of composite indicators is considered to be a best approach for sustainability evaluation. to do this, the current problems of Hanoi groundwater resources were carefully reviewed and explored to propose three main aspects （quantity, quality and management） and appropriately construct their 9 MESIs （Macroeconomic Sustainability Indicators）. As for the results, the sustainability indices of the quantity, quality and management aspects were appropriately assessed as good, excellent and good sustainability levels, respectively. As a result, the sustainability of Hanoi groundwater resources development is economically good, indicating that there has been a big effort to improve the groundwater sustainability from both sides, the local government and communities.

关键词： Groundwater MESI sustainability assessment AHP Hanoi.

Comparing the Soil Conservation Service model with new machine learning algorithms for predicting cumulative infiltration in semi-arid regions

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Pedosphere 2022年第5期32卷 718-732页

作者： Khabat KHOSRAVI Phuong t.t.NGO Rahim BARZEGAR John QUILtY Mohammad t.AALAMI Dieu t.bui Department of Watershed Management Engineering Ferdowsi University of MashhadMashhad 93(Iran) Department of Earth and Environment Florida International UniversityMiami 33199(USA) Institute of Research and Development Duy Tan UniversityDa Nang 550000(Vietnam) Department of Bioresource Engineering McGill UniversitySte Anne de Bellevue QC H9X(Canada) Faculty of Civil Engineering University of TabrizTabriz 51(Iran) Department of Civil and Environmental Engineering University of WaterlooWaterloo N2L 3G1(Canada) Department of Business and It University of South-Eastern NorwayNotodden 3603(Norway)

Water infiltration into soil is an important process in hydrologic cycle;however,its measurement is difficult,time-consuming and *** and physical models have been developed to predict cumulative infiltration(CI),but are often *** this study,several novel standalone machine learning algorithms(M5Prime(M5P),decision stump(DS),and sequential minimal optimization(SMO))and hybrid algorithms based on additive regression(AR)(i.e.,AR-M5P,AR-DS,and AR-SMO)and weighted instance handler wrapper(WIHW)(i.e.,WIHW-M5P,WIHW-DS,and WIHW-SMO)were developed for CI *** Soil Conservation Service(SCS)model developed by the United States Department of Agriculture(USDA),one of the most popular empirical models to predict CI,was considered as a ***,154 measurements of CI(explanatory/input variables)were taken from 16 sites in a semi-arid region of Iran(Illam and Lorestan provinces).Six input variable combinations were considered based on Pearson correlations between candidate model inputs(time of measuring and soil bulk density,moisture content,and sand,clay,and silt percentages)and *** dataset was divided into two subgroups at random:70%of the data were used for model building(training dataset)and the remaining 30%were used for model validation(testing dataset).the various models were evaluated using different graphical approaches(bar charts,scatter plots,violin plots,and taylor diagrams)and quantitative measures(root mean square error(RMSE),mean absolute error(MAE),Nash-Sutcliffe efficiency(NSE),and percent bias(PBIAS)).time of measuring had the highest correlation with CI in the study *** best input combinations were different for different *** results showed that all hybrid algorithms enhanced the CI prediction accuracy compared to the standalone *** AR-M5P model provided the most accurate CI predictions(RMSE=0.75 cm,MAE=0.59 cm,NSE=0.98),while the SCS model had the lowest performance(RMSE=4.77 cm,MAE=2.64 cm,NSE=

关键词： additive regression hybrid algorithms empirical model soil water infiltration weighted instances handler wrapper

Study the Hydration and the Microstructure of Cement Blended with Rice Husk Ash in Comparison with Silica Fume

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武汉理工大学学报 2010年第17期32卷 252-255,260页

作者： NGUYEN V t YE G VAN B K bui D D Faculty of Civil Engineering and Geosciences Delft University of TechnologyP.O. Box 50482600 GADelftThe Netherlands Department of building Materials Hanoi University of Civil EngineeringHanoi 700803Vietnam

Rice husk ask (RHA) is not a ultra-fine material as silica fume (SF),but possesses a very high specific surface area because of its porous structure. With the similar chemical composition of RHA and SF,the activity of RHA,therefore,is different from that of SF. the objective of this work is to study the hydration and the microstructure of Portland cement blended with RHA in comparison with SF. the test results show that SF refined the pore structure of cement paste better than RHA. However,the effect of RHA on cement hydration is more pronouned than that of SF for the mixture with low water to binder ratio.

关键词： hydration isothermal calorimetry mercury intrusion porosimetry (MIP) microstructure rice husk ash silica fume

Morpho-Physiological Changes in Roots of Rice Seedling upon Submergence

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Rice science 2019年第3期26卷 167-177页

作者： Liem t.bui Evangelina S.ELLA Maribel L.DIONISIO-SESE Abdelbagi M.ISMAIL Department of Plant Biotechnology Cuu Long Delta Rice Research Institute Crop and Environmental Sciences Division International Rice Research Institute Institute of Biological Sciences University of the Philippines Los Ba?os College

Submergence is a serious environmental condition that causes large loss in rice production in rain fed lowland and flood affected area. this study evaluated morphological and physiological responses of rice roots to submergence using two tolerant rice genotypes FR13A and Swarna-Sub 1 and two sensitive ones Swarna and IR42. the tolerant genotypes had higher survival rate and less shoot elongation but greater root elongation during submergence than the sensitive ones. After submergence,the tolerant genotypes also had higher root dry weight and more active roots than the sensitive *** genotypes exhibited less root injury, with less malondialdehyde production and slower electrolyte leakage after submergence. tolerant genotypes also maintained higher concentrations of soluble sugar and starch in roots and shoots and higher chlorophyll retention after submergence than the sensitive *** data showed that root traits such as root activity and root growth are associated with survival rate after submergence. this is probably accomplished through higher energy supply, and membrane integrity is necessary to preserve root function and reduce injury during submergence. these root traits are important for submergence tolerance in rice.

关键词： peroxidase root activity submergence rice seedling Sub1a gene

A tree-based intelligence ensemble approach for spatial prediction of potential groundwater

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International Journal of Digital Earth 2020年第12期13卷 1408-1429页

作者： Mohammadtaghi Avand Saeid Janizadeh Dieu tien bui Viet Hoa Pham Phuong thao t.Ngo Viet-Ha Nhu Faculty of Natural Resources and Marine Sciences Tarbiat Modares UniversityTehranIran Geographic Information Science Research Group Ton Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Environment and Labour Safety Ton Duc Thang UniversityHo Chi Minh CityVietnam Ho Chi Minh City Institute of Resources Geography Vietnam Academy of Science and TechnologyHo Chi Minh CityVietnam Institute of Research and Development Duy Tan UniversityDa NangVietnam Department of Geological-Geotechnical Engineering Hanoi University of Mining and GeologyHanoiVietnam

the objective of this research is to propose and confirm a new machine learning approach of Best-First tree(BFtree),AdaBoost(AB),MultiBoosting(MB),and Bagging(Bag)ensembles for potential groundwater mapping and assessing role of influencing *** Yasuj-Dena area(Iran)is selected as a case *** this regard,a Yasuj-Dena database was established with 362 springs locations and 12 groundwater-influencing factors(slope,aspect,elevation,stream power index(SPI),length of slope(LS),topographic wetness index(tWI),topographic position index(tPI),land use,lithology,distance from fault,distance from river,and rainfall).the database was employed to train and validate the proposed groundwater *** area under the curve(AUC)and statistical metrics were employed to check and confirm the quality of the *** result shows that the BFtree-Bag model(AUC=0.810,kappa=0.495)has the highest prediction performance,followed by the BFtree-MB model(AUC=0.785,kappa=0.477),and the BFtree-MB model(AUC=0.745,kappa=0.422).Compared to the benchmark of Random Forests,the BFtree-Bag model performs better;therefore,we conclude that the BFtree-Bag is a new tool should be used for modeling of groundwater potential.

关键词： Environmental modeling groundwater potential GIS ensemble model decision tree

A comparative study of three different learning algorithms applied to ANFIS for predicting daily suspended sediment concentration

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International Journal of Sediment Research 2017年第3期32卷 340-350页

作者： Keivan Kaveh Minh Duc bui Peter Rutschmann Department of hydraulic and water resource engineering/School of civil engineering Technische Universitt Mnchen (TUM)

the modeling and prediction of suspended sediment in a river are key elements in global water recourses and environment policy and management. In the present study, an Adaptive Neuro-Fuzzy Inference System model trained with the Levenberg-Marquardt learning algorithm is considered for time series modeling of suspended sediment concentration in a river. the model is trained and validated using daily river discharge and suspended sediment concentration data from the Schuylkill River in the United States. the results of the proposed method are evaluated and compared with similar networks trained with the common Hybrid and Back-Propagation algorithms, which are widely used in the literature for prediction of suspended sediment concentration. Obtained results demonstrate that models trained with the Hybrid and Levenberg-Marquardt algorithms are comparable in terms of prediction ***, the networks trained with the Levenberg-Marquardt algorithm perform better than those trained with the Hybrid approach.

关键词： Fuzzy Inference System Hybrid learning rule Levenberg-Marquardt algorithm Schuylkill river Suspended sediments

A Free Streaming Contact Preserving Scheme for the M_(1) Model

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Advances in Applied Mathematics and Mechanics 2010年第3期2卷 259-285页

作者： C.Berthon J.Dubois B.Dubroca t.-H.Nguyen-bui R.turpault Universitéde Nantes Laboratoire de Mathématiques Jean Leray2 Rue de la Houssinière 44322 Nantes Cedex 3France CEA CESTA33114 Le BarpFrance UniversitéBordeaux I CELIA351 Cours de la libération33405 Talence CedexFrance

the present work concerns the numerical approximation of the M_(1) model for radiative *** main purpose is to introduce an accurate finite volume method according to the nonlinear system of conservation laws that governs this *** propose to derive an HLLC method which preserves the stationary contact *** supplement this essential property,the method is proved to be robust and to preserve the physical admissible ***,a relevant asymptotic preserving correction is proposed in order to obtain a method which is able to deal with all the physical *** relevance of the numerical procedure is exhibited thanks to numerical simulations of physical interest.

关键词： Radiative transfer equation M_(1)model finite volume method Riemann solver HLLC scheme asymptotic preserving scheme